Tattoos have long been used by law enforcement to help identify criminals and victims, as well as for investigative research purposes.

However, the ANSI-NIST-ITL 1-2011 standard that is used to collect and assign keyword labels to tattoos has many limitations, such as the need for many keywords to accurately describe some tattoos, and subjectivity in labelling the same tattoo differently between examiners.

This drawback of keyword-based tattoo image retrieval has led to a crucial need for automated image-based tattoo recognition capabilities.

Since tattoo recognition is a relatively new industry, there is no common test data and use cases available to evaluate and develop systems for next generation government applications.

To remedy this, the Tatt-C dataset was developed as an initial tattoo test corpus that addresses use cases taken from operational scenarios provided by the FBI’s Biometric Center of Excellence.

The R&D project strives to determine which algorithms are most effective and whether any could be used in five different operational use-cases, including tattoo similarity, tattoo identification, region of interest, mixed media, and tattoo detection.

Those interested parties are asked to contact the NIST if they are a developer of tattoo matching algorithms or are interested in developing them, if they represent an organization that have suitable tattoo datasets that might be valuable to the NIST’s efforts, or if they have an operational interest or need for image-based matching of tattoo images.